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UNIVERSITI PUTRA MALAYSIA
EHSAN MOAZAMI
FK 2013 67
MULTI-OBJECTIVE SERVICE RESTORATION IN DISTRIBUTION NETWORKS USING GENETIC ALGORITHM
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MULTI-OBJECTIVE SERVICE RESTORATION IN DISTRIBUTION
NETWORKS USING GENETIC ALGORITHM
By
EHSAN MOAZAMI
Thesis Submitted to the School of Graduate Studies, Universiti Putra
Malaysia, in Fulfilment of the Requirements for the Degree of Master of
Science
April 2013
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Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment
of the requirement for the degree of Master of Science
MULTIOBJECTIVE SERVICE RESTORATION IN DISTRIBUTION
NETWORKS USING GENETIC ALGORITHM
By
EHSAN MOAZAMI
April 2013
Chairman : Professor Mohd. Zainal Abidin Ab Kadir, PhD PEng
Faculty : Engineering
Electricity is the backbone of each industrialised society and economy. Modern
countries are not used to having even short power blackouts. As an effective post-
fault supply restoration strategy for distribution networks plays a key part in
improving service reliability and enhancing customer satisfaction, where there has
been considerable research effort focused on this problem. The main challenge has
been in reducing the search space so as to achieve an optimal solution within an
acceptable computing burden. Furthermore, restoration is a multi-objective problem
that used for solving the minimization of out of service area, minimization of
switching operation and minimization of power loss whilst considering the technical
constraints. This thesis presents a new approach of supply restoration service using
the Genetic Algorithm. The GA is robust in searching a global optimal solution for
the large-scale combinatorial optimization problems. A new hybrid Genetic
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Algorithm is proposed for reducing the search space and execution burden in solving
the supply restoration problems.
A proposed algorithm is investigated for radiality checking that is found very
efficient in distribution restoration problems. Another proposed technique is
implemented to improve the penalty strategy to enhance the performance of
algorithm and reduce the convergence iteration. The effectiveness of the proposed
method is demonstrated by testing on two case studies, a 33-bus test system and a 16
bus test system. Then the results are compared with the previous works all using GA
in restoration. Comparisons show the improvements in reducing of number of
iteration and fulfilling the radiality of the system after restoration. Findings through
comparisons are shown that the proposed method will be able to do full restoration
and energize all loads. Also, full reenergizing of all loads as the most important
objective function is satisfied with less number of switching and better voltage
profile. According to the comparison of the result of thesis with other previous work,
it can be observed that reducing the number of iteration is significantly reduced.
Results shows very low iteration number and low computation burden compare to
other previous works.
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Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai
memenuhi keperluan untuk ijazah Master Sains
PEMULIHAN PERKHIDMATAN OBJEKTIF-PELBAGAI DI DALAM
RANGKAIAN PENGAGIHAN MENGGUNAKAN ALGORITMA GENETIK
Oleh
EHSAN MOAZAMI
April 2013
Pengerusi : Profesor Mohd. Zainal Abidin Ab Kadir, PhD PEng
Fakulti : Kejuruteraan
Elektrik merupakan tunjang utama kepada setiap industri dan ekonomi. Negara-
negara maju akan memastikan tiada gangguan bekalan kuasa walaupun dalam
jangkamasa pendek. Sebagai strategi pemulihan bekalan yang berkesan untuk sistem
pengagihan selepas gangguan bekalan, ianya memainkan peranan yang penting
dalam meningkatkan kebolehpercayaan perkhidmatan dan meningkatkan tahap
kepuasan pelanggan, di mana terdapat usaha penyelidikan yang memberangsangkan
ke arah permasalahan tersebut. Cabaran utama adalah dalam mengurangkan ruang
carian bagi mencapainya satu penyelesaian yang optimum dalam beban
pengkomputeran yang boleh diterima. Tambahan pula, pemulihan adalah masalah
multi-objektif yang digunakan untuk menyelesaikan pengurangan kehilangan kuasa
disamping mempertimbangkan kekangan teknikal. Tesis ini membentangkan satu
pendekatan baru perkhidmatan pemulihan bekalan menggunakan algoritma genetik
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(GA). GA ini cekap dalam mencari penyelesaian global yang optimum bagi masalah
kombinasi optimum yang berskala besar.
Sebuah algoritma genetik hibrid yang baru telah dicadangkan untuk mengurangkan
ruang carian dan beban pelaksanaan dalam menyelesaikan masalah pemulihan
bekalan. Algoritma yang dicadangkan ini disiasat untuk semakan radialiti yang
dilihat sangat berkesan dalam pemulihan masalah. Teknik yang dicadangkan telah
dilaksanakan untuk meningkatkan strategi penalti untuk memangkin prestasi
algoritma dan mengurangkan pengulangan pemusatan. Keberkesanan kaedah yang
dicadangkan ini ditunjukkan dengan ujian yang dijalankan terhadap dua kajian kes
iaitu sistem ujian 33-bus dan sistem ujian 16-bus. Seterusnya, keputusan yang
diperolehi dibandingkan dengan kerja-kerja sebelum ini yang menggunakan GA
dalam pemulihan. Perbandingan menunjukkan peningkatan dalam pengurangan
bilangan pengulangan dan memenuhi radialiti sistem selepas pemulihan. Keputusan
melalui perbandingan menunjukkan bahawa kaedah yang dicadangkan dapat
melakukan pemulihan penuh dan penyaluran tenaga kepada semua beban. Di
samping itu, pemulihan semula tenaga penuh pada semua beban merupakan objektif
terpenting yang memuaskan dengan pengurangan bilangan pertukaran dan profil
voltan yang lebih baik.
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ACKNOWLEDGEMENTS
In the Name of Allah, the Most Compassionate, the Most Merciful.
First, I would like to express my thanks and deepest gratitude to my supervisor,
Professor Dr. Mohd. Zainal Abidin Ab Kadir for his invaluable help, guidance,
supervision and constant encouragement throughout my dissertation. Thanks to co-
supervisor, Associate Professor Dr. Hashim Hizam for his useful comments and
advices in this project.
I would also like to acknowledge my wife for her moral support and
encouragements.
Finally, I am indebted to my lovely parent for their supports and dedications.
Thank you and May God reward them all.
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I certify that a Thesis Examination Committee has met on 4/9/2013 to conduct the
final examination of Ehsan Moazami on his thesis entitled “Multiobjective Service
Restoration in Distribution Networks Using Genetic Algorithm” in accordance
with the Universities and University Colleges Act 1971 and the Constitution of the
Universiti Putra Malaysia [P.U.(A)] 15 March 1998. The committee recommends
that the student be awarded Master of Science.
Members of the Thesis Examination Committee were as follows:
Nasri b. Sulaiman, PhD
Faculty of Engineering
Universiti Putra Malaysia
(Chairman)
Ishak b. Aris, PhD
Professor
Faculty of Engineering
Universiti Putra Malaysia
(Internal Examiner)
Wan Fatinhamamahbt. Wan Ahmad, PhD
Faculty of Engineering
Universiti Putra Malaysia
(Internal Examiner)
Muhammad Murtadha b. Othman, PhD
Faculty of Electrical Engineering
UniversitiTeknologi MARA
(External Examiner)
NORITAH OMAR, PhD
Associate Professor and Deputy Dean
School of Graduate Studies
Universiti Putra Malaysia
Date: 2 August 2013
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This thesis was submitted to the Senate of Universiti Putra Malaysia and has been
accepted as fulfilment of the requirement for the degree of Master of Science. The
members of the Supervisory Committee were as follows:
Mohd. Zainal Abidin Ab Kadir, PhD
Professor
Faculty of Engineering
Universiti Putra Malaysia
(Chairman)
Hashim Hizam, PhD
Associate Professor
Faculty of Engineering
Universiti Putra Malaysia
(Member)
___________________________________
BUJANG BIN KIM HUAT, PhD
Professor and Dean
School of Graduate Studies
Universiti Putra Malaysia
Date:
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DECLARATION
I declare that the thesis is my original work except for quotations and citations which
have been duly acknowledged. I also declare that it has not been previously, and is
not concurrently submitted for any other degree at Universiti Putra Malaysia or at
any other institutions.
____________________________________
EHSAN MOAZAMI
Date: 29 April 2013
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TABLE OF CONTENTS
Page
ABSTRACT i
ABSTRAK iii
ACKNOWLEDGEMENT v
APPROVAL vi
DECLARATION viii
LIST OF TABLES xii
LIST OF FIGURES xiv
LIST OF ABBREVATIONS xvi
CHAPTER
1 INTRODUCTION 1 1.1 Overview 1 1.2 Problem Statement 3 1.3 Objectives 6 1.4 Scope of Research 6 1.5 Thesis Outlines 7
2 LITERATURE REVIEW 9 2.1 Introduction 9 2.2 Blackouts Problems and Urgency of Fast Restoration 10 2.3 Distribution System Restoration 14
2.3.1 Current Restoration Practice in the World 17 2.3.2 Malaysian Utility Restoration Practice 17
2.4 Investigating of Restoration Practice in Different
Countries 18 2.5 General Review of Service Restoration Techniques 19
2.5.1 Mathematical Programming 19 2.5.2 Knowledge Based 21 2.5.3 Meta-heuristic methods 23
2.6 Genetic Algorithm 28 2.7 Multi-objective Genetic Algorithms 34
2.8 Radiality Constraint in Distribution Restoration 35
2.8.1 Graph Theory and Application 39
2.9 Penalty Method 41 2.10 Simulation and Modelling Tools 43
2.10.1 PSAT vs. Other Matlab Toolboxes 44 2.11 Summary 45
3 METHODOLOGY 46 3.1 Introduction 46
3.2 Distribution System Modelling 52
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3.3 Distribution System Restoration 54 3.3.1 Objective Function Formulation 55 3.3.2 Constraints 57 3.3.3 Mathematical Formulation of Load Flow 59
3.4 Methodology of Genetic Algorithm 61 3.4.1 Initial Population 64 3.4.2 Fitness Function 65 3.4.3 Proposed Method for Radiality Checking 67 3.4.4 Penalty Method for Evaluation of Inappropriate
Solutions 71 3.4.5 String Selection 75 3.4.6 Crossover Operation 77
3.4.7 Mutation Operation 79 3.4.8 Considering on the integration between power
flow software and the proposed algorithm (Based
on GA) 81 3.5 Genetic Algorithm parameter setting 82 3.6 Summary 86
4 RESULT AND DISCUSSION 87 4.1 Introduction 87 4.2 Three Feeder 16 Bus Radial Distribution Test System 88
4.2.1 Simulation of Three Feeder 16 Bus Radial
Distribution Test System 88 4.2.2 Power Flow Analysis of Three Feeder 16 Bus
Radial Distribution Test System 89 4.3 Single Feeder 33 Bus Radial Distribution Test System 92
4.3.1 Simulation of Single Feeder 33 Bus Radial
Distribution Test System 93 4.3.2 Power Flow Analysis of Single Feeder 33 Bus
Radial Distribution Test System 95 4.4 Result of Implementing the Proposed Algorithm to the
Multi-objective Optimization Service Restoration in
Genetic Algorithm 97 4.4.1 Result of Implementing the Proposed Algorithm
to 16 Bus Radial Distribution System 97 4.4.2 Result of Implementing the Proposed Algorithm
to 33 Bus Radial Distribution System 103
4.5 Comparison of Result of the Proposed Method with
Past Works in Restoration Problem 111 4.6 Compatibility of the Algorithm with Different
Parameters Setting 114 4.7 Compatibility of the Algorithm with Different
Weighting Value 115 4.8 Compatibility of the Algorithm with Different Fault
Locations 117
4.9 Characteristics of GA Convergence 117
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4.10 Summary 120
5 CONCLUSION AND FUTURE WORKS 121 5.1 Conclusion 121 5.2 Future Research 122
REFERENCES 124
APPENDICES 132 Appendix A 132 Appendix B 144 Appendix C 150 Appendix D 157